System and method for improved obstructive sleep apnea diagnostic for implantable devices

ABSTRACT

A system and method of diagnosing sleep apnea including an implantable device with a sensor, a telemetry circuit and a memory, an external programmer in communication with the telemetry circuit and configured to receive data collected by the sensor and stored in the memory. The system and method include operation of a server, including a processor, in communication with the external programmer and storing an application including instructions that when executed by the processor executes steps of receiving the data collected by the sensor from the external programmer, analyzing the received data collected by the sensor, and transmitting to a remote computer an assessment of the received sensor data, wherein the assessment includes an evaluation of sleep apnea for the patient.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to U.S. Provisional Application No.62/814,398 filed Mar. 6, 2019 and entitled INTRAMUSCULAR HYPOGLOSSALNERVE STIMULATION FOR OBSTRUCTIVE SLEEP APNEA THERAPY, the entirecontents of which are incorporated herein by reference.

TECHNICAL FIELD

This disclosure relates to implantable medical device systems andmethods of assessing physiological data to diagnose sleep apnea.

BACKGROUND

Implantable medical devices capable of delivering electrical stimulationpulses have been proposed or are available for treating a variety ofmedical conditions, such as cardiac arrhythmias and chronic pain asexamples. Sleep apnea is generally separated into two forms obstructivesleep apnea (OSA) and central sleep apnea (CSA). Sleep apnea is aserious disorder in which breathing is irregularly and repeatedlystopped and started during sleep, resulting in disrupted sleep andreducing blood oxygen levels. OSA is caused by complete or partialcollapse of the pharynx during sleep. In particular, muscles in apatient's mouth and throat intermittently relax thereby obstructing theupper airway while sleeping. Airflow into the upper airway can beobstructed by the tongue or soft pallet moving to the back of the throatand covering a smaller than normal airway. Loss of air flow also causesunusual inter-thoracic pressure as a person tries to breathe with ablocked airway. In contrast CSA is generally the result of the cessationof respiratory drive. That is, the brain fails to provide the necessarysignals to your diaphragm and other muscles to engage in breathing.Regardless in both OSA and CSA Lack of adequate levels of oxygen duringsleep can contribute to abnormal heart rhythms, heart attack, heartfailure, high blood pressure, stroke, memory problems and increasedaccidents. Indeed, sleep apnea has a high rate of co-morbidity with manyforms of heart disease and particularly cardiac rhythm disease.Additionally, loss of sleep occurs when a person is awakened during anapneic episode.

SUMMARY

One aspect of the disclosure is directed to a method of assessing apatient for sleep apnea including: receiving sensor data from a deviceimplanted in a patient for treatment of a heart related disease at anexternal programmer; transmitting the received sensor data to a remoteserver; analyzing the received data at the server; and transmitting to aremote computer an assessment of the received sensor data, where theassessment includes an evaluation of sleep apnea for the patient. Otherembodiments of this aspect include corresponding computer systems,apparatus, and computer programs recorded on one or more computerstorage devices, each configured to perform the actions of the methodsand systems described herein.

Implementations of this aspect of the disclosure may include one or moreof the following features. The method further including receiving sensordata from an external sensor. The method further including receivingself-reported data. The method where the sensor data includes dataindicative of the posture of the patient, motion data of the patient,electroencephalogram (EEG) data, electrocardiogram (ECG) data, apneahypopnea index (AHI) data or blood-oxygen saturation data. The methodwhere the sensor data includes data from one or more three-axisaccelerometers. The method where the sensor data includes respirationrate data, heart rate data, total sleep time data, sleep efficiencydata, sleep stage data, arousals data, or awakenings data. The methodwhere the implanted device selected from the group including of apacemaker, an implantable cardiac defibrillators (ICD), a cardiacresynchronization therapy (CRT) device, and an implantableneurostimulator (INS). The method further including a neural networkperforming the analysis of the received data. The system furtherincluding one or more external sensors configured to transmit sensordata to the server or the external programmer. The system furtherincluding a user-interface presented on the external programmer andconfigured to receive self-reported data. The system where the sensoroutputs data indicative of the posture of the patient, motion of thepatient, an electroencephalogram (EEG), an electrocardiogram (ECG), anapnea hypopnea index (AHI) or blood-oxygen saturation. The system wherethe sensor is included of one or more three-axis accelerometers. Thesystem where the sensor outputs data indicative of respiration rate,heart rate, total sleep time, sleep efficiency, sleep stage, arousals,or awakenings. The system where the implanted device selected from thegroup including of a pacemaker, an implantable cardiac defibrillators(ICD), a cardiac resynchronization therapy (CRT) device, and animplantable neurostimulator (INS). The system further including a neuralnetwork performing the analysis of the received data at the server,

A further aspect of the disclosure is directed to a system including: animplantable device including a sensor, a telemetry circuit and a memory;an external programmer in communication with the telemetry circuit andconfigured to receive data collected by the sensor and stored in thememory; a server, including a processor, in communication with theexternal programmer and storing thereon an application includingInstructions that when executed by the processor executes steps of. Thesystem also includes receiving the data collected by the sensor from theexternal programmer. The system also includes analyzing the receiveddata collected by the sensor. The system also includes transmitting to aremote computer an assessment of the received sensor data, where theassessment includes an evaluation of sleep apnea for patient in whichthe implantable device has been implanted. Other embodiments of thisaspect include corresponding computer systems, apparatus, and computerprograms recorded on one or more computer storage devices, eachconfigured to perform the actions of the methods and systems describedherein.

Yet a further aspect of the disclosure is directed to a computerreadable recording medium storing thereon instructions that whenexecuted by a processor and cause the processor to execute the steps of:receiving sensor data from an external processor, the sensor data havingbeen collected by an implanted device configured for treatment of aheart related disease; analyzing the received sensor data; andtransmitting to a remote computer an assessment of the received sensordata, where the assessment includes an evaluation of sleep apnea for apatient in which the implantable device has been implanted. Otherembodiments of this aspect include corresponding computer systems,apparatus, and computer programs recorded on one or more computerstorage devices, each configured to perform the actions of the methodsand systems described herein.

Implementations of this aspect of the disclosure may include one or moreof the following features. The computer readable recording medium wherethe sensor data includes data indicative of the posture of the patient,motion data of the patient, electroencephalogram (EEG) data,electrocardiogram (ECG) data, apnea hypopnea index (AHI) data orblood-oxygen saturation data. The computer readable recording mediumwhere the sensor data includes data from one or more three-axisaccelerometers. The computer readable recording medium where the sensordata includes respiration rate data, heart rate data, total sleep timedata, sleep efficiency data, sleep stage data, arousals data, orawakenings data. Implementations of the described techniques may includehardware, a method or process, or computer software on acomputer-accessible medium, including software, firmware, hardware, or acombination of them installed on the system that in operation causes orcause the system to perform the actions. One or more computer programscan be configured to perform particular operations or actions by virtueof including instructions that, when executed by data processingapparatus, cause the apparatus to perform the actions.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a conceptual diagram of an implantable device in accordancewith one aspect of the disclosure;

FIG. 2 is a conceptual diagram of a system in accordance with thepresent disclosure; and

FIG. 3 depicts a flow chart for collecting, transmitting, and analyzingdata derived from the implantable device of FIG. 1.

DETAILED DESCRIPTION

This disclosure is directed to systems and methods of improved sleepapnea diagnosis and monitoring using data collected from implanteddevices.

As noted above, many forms of heart disease are co-morbid with sleepapnea. Typically sleep apnea is diagnosed using a sleep study orpolysomnography (PSG). A typical PSG requires at least six hours of datacollection and is usually undertaken in a clinical environment. As partof a PSG a variety of data is collected including anelectroencephalogram (EEG) data (brain wave activity), anelectroculogram (EOG) data (measuring eye and chin movements),electrocardiogram (ECG) data (heart rate and rhythm), respiration ratedata, and blood oxygen saturation level data, airflow from the nose andmouth, and leg movement data, and snoring data. From these data furtherobservations and determinations can be made including total sleep time(TST), sleep efficiency and latency (total sleep time compared to totalrecording time), sleep states, number of arousals (wakefulness less than15 seconds), awakenings (wakefulness greater than 15 seconds), an ApneaHypopnea Index (AHI) value.

The AHI is the number of apneas or hypopneas recorded during the studyper hour of sleep. It is generally expressed as the number of events perhour. Based on the AHI, the severity of OSA is classified as follows inTable 1:

TABLE 1 Severity Events None/Minimal: <5 per hour Mild: >5, but <15 perhour Moderate: ≥15, but <30 per hour Severe: ≥30 per hour

While such PSG testing is the gold standard for determining whether apatient suffers from sleep apnea, this testing has a number ofdisadvantages. First, the patient themselves may not have a clearunderstanding that that they suffer from sleep apnea and may not seekout testing. Indeed, one of the oft reported reasons that a patientseeks testing is due to pressure from a spouse or partner who themselvesmay be suffering from the patient's snoring and other sleep apneaactivities. Second, while the testing is being constantly monitored andthe sleep conditions are being monitored, the recording must necessarilybe done in an environment that is unfamiliar to the patient (resultingis potentially biased results). Third, due to all of the equipment beingemployed, the variety of wires, electrodes, and sensors can beuncomfortable and result in poor sleep. Finally, this type of testingwith all of the equipment involved, the need for constant monitoring,and the time and expertise necessary to analyze the data can be quiteexpensive.

A wide variety of implantable devices are employed in assessing andapplying therapy to patients suffering from various conditions. Commonimplantable devices include pacemakers, an implantable cardiacdefibrillators (ICD), and cardiac resynchronization therapy (CRT)devices. In the case of pacemakers and ICDs these may be either singleor dual chamber devices. In addition, more recently there have beendeveloped implantable neurostimulators such as those used for thetreatment of OSA by delivering therapy directly to the lingual musclesof a patient's tongue. All these implantable devices include a varietyof sensors to collect various physiological data from the patient.Utilization of the data generated by these implantable devices providesan improved and largely automated system and method of assessing sleepapnea in patients having these implantable devices and is described ingreater detail below.

FIG. 1 is a schematic diagram of an implantable device 10 in accordancewith the disclosure. Implantable device 10 includes a control circuit20, memory 30, therapy delivery circuit 40, a sensor 50, telemetrycircuit 60 and power source 70. Power source 70 may include one or morerechargeable or non-rechargeable batteries for supplying electricalcurrent to each of the control circuit 20, memory 30, therapy deliverycircuit 40, sensor 50 and telemetry circuit 60. While power source 70 isshown in communication only with control circuit 20 for the sake ofclarity, it is to be understood that power source 70 provides power asneeded to each of the circuits and components of implantable device 10as needed. For example, power source 70 provides power to therapydelivery circuit 40 for generating electrical stimulation pulses.

Sensor 50 may include one or more separate sensors for monitoring apatient condition. These sensors may include one or accelerometers,inertial measurement units (IMU), fiber-Bragg gratings (e.g., shapesensors), optical sensors, acoustic sensors, pulse oximeters, and otherswithout departing from the scope of the disclosure and as will bedescribed in greater detail below.

The functional blocks shown in FIG. 1 represent functionality includedin an implantable device 10 such as those described above. Theimplantable device 10 may include any discrete and/or integratedelectronic circuit components that implement analog and/or digitalcircuits capable of producing the functions attributed to a pulsegenerator herein. The various components may include an applicationspecific integrated circuit (ASIC), an electronic circuit, a processor(shared, dedicated, or group) and memory that execute one or moresoftware or firmware programs, a combinational logic circuit, statemachine, or other suitable components or combinations of components thatprovide the described functionality. Providing software, hardware,and/or firmware to accomplish the described functionality in the contextof any modern medical device system, given the disclosure herein, iswithin the abilities of one of skill in the art.

Control circuit 20 communicates, e.g., via a data bus, with memory 30,therapy delivery circuit 40, telemetry circuit 60 and sensor 50 tocontrol the delivery of therapy other functions. As disclosed herein,control circuit 20 may pass control signals to therapy delivery circuit40 to cause therapy delivery circuit 40 to deliver electricalstimulation pulses via electrodes 80 a-80 d according to a therapyprotocol. Control circuit 20 may further be configured to pass therapycontrol signals to therapy delivery circuit 40 including stimulationpulse amplitude, stimulation pulse width, stimulation pulse number andfrequency of a stimulation pulse train.

Memory 30 may store instructions for execution by a processor includedin control circuit 20, stimulation control parameters, and otherdevice-related or patient-related data. Control circuit 20 may retrievetherapy delivery control parameters and a therapy delivery protocol frommemory 30 to enable control circuit 20 to pass control signals totherapy delivery circuit 40 for controlling therapy. Memory 30 may storehistorical data relating to therapy delivery for retrieval by a user viatelemetry circuit 60. Therapy delivery data or information stored inmemory 30 may include therapy control parameters used to deliverstimulation pulses as well as delivered therapy protocol(s), hours oftherapy delivery or the like. Patient related data, such as thatreceived from the sensor 50 signal may be stored in memory 30 forretrieval by a user or other system components as described in greaterdetail below.

Therapy delivery circuit 40 may include a charging circuit 42, an outputcircuit 44, and a switching circuit 46. Charging circuit 42 may includeone or more holding capacitors that are charged using a multiple of thebattery voltage of power source 70, for example. The holding capacitorsare switchably connected to output circuit 44, which may include one ormore output capacitors that are coupled to a selected bipolar electrodepair via switching circuit 46. The holding capacitor(s) are charged to aprogrammed pacing pulse voltage amplitude by charging circuit 42 anddischarged across the output capacitor for a programmed pulse width.Charging circuit 42 may include capacitor charge pumps or an amplifierfor the charge source to enable rapid recharging of holding capacitorsincluded in charging circuit 42. Therapy delivery circuit 40 responds tocontrol signals from control circuit 20 for generating and deliveringtrains of pulses as therapeutic pulses to the electrodes 80 a-80 d.

Output circuit 44 may be selectively coupled to bipolar pairs ofelectrodes 80 a-80 d via switching circuit 46. Switching circuit 46 mayinclude one or more switches activated by timing signals received fromcontrol circuit 20. Electrodes 80 a-80 d may be selectively coupled tooutput circuit 44 in a time-varying manner to deliver stimulation todifferent portions of the protrusor muscles at different time to avoidfatigue, without requiring stimulation to be withheld completely.Switching circuit 46 may include a switch array, switch matrix,multiplexer, or any other type of switching device(s) suitable toselectively couple therapy delivery circuit 40 to electrodes 80 a-80 d.

Telemetry circuit 60 may be included to enable bidirectionalcommunication with an external programmer 90. A user, such as thepatient, may manually adjust therapy control parameter settings, e.g.,as described in Medtronic's Patient Programmer Model 37642, incorporatedby reference in its entirety. The patient may make limited programmingchanges such as small changes in pulse amplitude and pulse width. Thepatient may turn the therapy on and off or to set timers to turn thetherapy on or off using external programmer 90 in wireless telemetriccommunication with telemetry circuit 60.

In other examples, a user, such as a clinician, may interacts with auser interface of an external programmer 90 to program implantabledevice 10 according to a desired therapy protocol. For example, aPhysician Programmer Model 8840 available from Medtronic, Inc.,Minneapolis, Minn., may be used by the physician to program theimplantable device 10.

Programming of implantable device 10 may refer generally to thegeneration and transfer of commands, programs, or other information tocontrol the operation of the implantable device 10. For example,external programmer 90 may transmit programs, parameter adjustments,program selections, group selections, or other information to controlthe operation of implantable device 10, e.g., by wireless telemetry. Asone example, external programmer 90 may transmit parameter adjustmentsto support therapy changes. As another example, a user may selectprograms or program groups. A program may be characterized by anelectrode combination, electrode polarities, voltage or currentamplitude, pulse width, pulse rate, therapy duration, and/or pattern ofelectrode selection for delivering patterns of alternating portions ofthe protrusor muscles that are being stimulated. A group may becharacterized by multiple programs that are delivered simultaneously oron an interleaved or rotating basis. These programs may adjust outputparameters or turn the therapy on or off at different time intervals.

In some cases, external programmer 90 may be characterized as aphysician or clinician programmer if it is primarily intended for use bya physician or clinician. In other cases, external programmer 90 may becharacterized as a patient programmer if it is primarily intended foruse by a patient. A patient programmer 90 is generally accessible topatient and, in many cases, may be a portable device that may accompanythe patient throughout the patient's daily routine. In general, aphysician or clinician programmer may support selection and generationof programs by a clinician for use by implantable device 10, whereas apatient programmer may support adjustment and selection of such programsby a patient during ordinary use.

External programmer 90 may present patient related and/or device relateddata retrieved from memory 30 via telemetry circuit 60. For example, thepatient related data may be a variety of sensor data received fromsensor 50 and stored in memory 40. These data may be presented on one ormore user interfaces via a display found on the external programmer 90or in communication with the external programmer.

As will be apparent to those of skill in the art, the sensor 50, whichmay of course be any number of separate sensors, is a significant aspectof the disclosure. For example, the sensor 50 may be a blood-oxygensaturation sensor. This may be an optical sensor and configured aseither a reflectance blood-oxygen saturation sensor or a transmissiveblood-oxygen saturation sensor. In the case of the transmissiveblood-oxygen sensor a light source may be formed as part of a cuffdesigned to surround a blood vessel. A photodetector may be configuredon an opposite side of the cuff from the light source. Otherconfigurations of the blood-oxygen saturation sensor either within abody of the implantable device 10 or operably connected there are alsoconsidered within the scope of the disclosure. Indeed, in accordancewith the disclosure, the blood-oxygen saturation sensor may be entirelyseparate from the implantable device 10 and simply an external sensorapplied to the finger of the patient, but in communication with theexternal programmer 90.

A further sensor 50 may be a motion detector. The motion detector may bean accelerometer, for example a three-axis accelerometer. This motiondetector may be tuned to detect motion caused by movement of thepatient, motion caused by the beating of the heart (e.g., measuring thepatient's pulse), or motion caused by respiration (operation of thelungs) and others. For example, the sensor 50 may be tuned to detectmovement of the patient's legs. In accordance with one aspect of thedisclosure this might be detected motion that which is inconsistent withheart rate movement or respiration movement and does not result in achange in posture of the patient. Still further, the three-axisaccelerometer may be tuned to detect snoring. Again, band pass filteringcan be employed to remove all but the high frequency input that isassociated with snoring.

The sensor 50 may be a posture detector. As a posture detector, athree-axis accelerometer can be employed to detect when the patient isin a reclined or sleeping position and even whether the patient islaying prone or supine or laying on their right or left sides. Theeffect of 1G of gravitational acceleration applied directly along anaxis of a stationary accelerometer provides a characteristic outputvoltage signal having an amplitude that can be referenced or scaled as+1 for angular computation purposes. The effect of 1 G of gravitationalacceleration applied in precisely the opposite or negative direction tothe sensitive axis provides a characteristic output voltage signalamplitude that is referenced or scaled as −1. If the axis is orientedtransverse to the direction of the gravitational force, a bias voltagelevel output signal should be present, and that voltage signal level isreferenced or scaled as 0. The degree to which the axis is oriented awayor tilted from the direction of the gravitational force can also bedetected by the magnitude and polarity of the output voltage signallevel deviating from the bias level scaled to 0 and below the outputsignal level values scaled to +1 and −1. Other scales may be employed,depending on the signal polarities and ranges employed. The sensor 50may include its own microprocessor with autocalibration of offset errorand drift (possibly caused by temperature variation or other things).

TABLE 2 Posture a_(x) a_(y) a_(z) UP 0 +1 0 SUPINE 0 0 +1 PRONE 0 0 −1RIGHT −1 0 0 LEFT +1 0 0

Table 2 sets forth the ideal, scaled amplitudes of the output signals,ax, ay, and az, respectively, of a three-axis accelerometer employed insensor 50 and incorporating into implantable device 10. (The units inthe ideal example would be in gravity or “g”). One axis of theaccelerometer (a_(y)) is aligned to earth's gravitational field when theimplantable device 10 is implanted. Thus, when standing upright andremaining still, the amplitude or level of the output signal a_(y) ofthree-axis accelerometer should be at +1. In this orientation, thescaled amplitudes of the output signals az and ax of the three-axisaccelerometer, respectively, should approach 0.

The scaled amplitude of the output signal az of the three-axisaccelerometer should approach +1 or −1, respectively, when the patientlies still and is either supine or prone on their back or stomach and ifthe INS 10 is implanted with the z-axis of the three axis accelerometeraligned in a posterior-anterior position. In these positions, theamplitudes of the output signals a_(y) and ax of the three-axisaccelerometer, respectively, should approach 0. In the same fashion, thepatient lying on the right and left sides will orient the sensitive axisof the three-axis accelerometer with earth's gravitational field todevelop the scaled amplitude of either −1 or +1 of the output signala_(x). The amplitudes of the output signals a_(y) and a_(z) of thethree-axis accelerometer should approach 0. In these ideal orientationsof Table 2, there is no rotation of the axes of the INS 10 with respectto earth's gravitational field.

As will be appreciated, the determination described above identifies thepose of the implantable device 10 and not necessarily the patient inwhich it is implanted. In practice the implantable device 10 will rarelyif ever be implanted in the patient such that the three axes of thethree-axis accelerometer precisely align the idea orientations ofTable 1. Accordingly, following implantation of the implantable device10, a series of calibration tests can be undertaken during which thepatient is alternated from standing to lying, from prone to supine, andfrom right to left sides. By acquiring a series of such values, thesensor 50 can be calibrated for the implantation, to determine thevoltage output values of each of the three axes of the accelerometer ineach of the positions. Further, though not described in detail herein,similar analyses may be undertaken to determine when a person is in aslightly reclined position such as when sitting in an airplane seat orother position.

In another sensor 50, a three-axis accelerometer acts, as noted above,as a motion detector. This motion detector is tuned (e.g., using one ormore band pass filters) to detect lung vibrations in the patient causedby respiration.

The sensor 50 may be an ECG sensor. ECG is a recording of the electricalactivity of the heart over a period of time. While an ECG typicallyemploys sensors placed on the skin, an effective ECG can be employed inan implantable device wherein at least two electrodes separated by adistance (e.g., at least about 35 mm) are employed to detect electricalchanges caused by the cardiac depolarization and repolarization duringeach cardiac cycle.

Yet a further sensor 50 that may be employed is an EEG system from whichthe sleep stages of the patient may be determined. The EEG may includesensors implanted in the patient and operably connected to theimplantable device 10. Alternatively, the sensors may be implanted inthe patient and operably connected to a remove or satellite implanteddevice located above the shoulders of the patient and in communicationwith the implantable device 10. Still further the sensors may be awearable set of sensors that are in communication with the implantabledevice.

In view of inclusion of one or more of these sensors 50, a corollary setof data can be constructed to that from a sleep study. For example, thetotal sleep time (TST) can be derived by comparing the time period thatthe patient (an implantable device 10) is in a lying down position,either prone or supine, and the time where the motion sensor detectsmotion consistent with a sleeping heart rate, or with motion consistentwith sleeping. Once a TST is determined, a sleep efficiency can also bederived by comparing the TST to the total recording time (TRT) which maybe the entirety of the period that the patient is in the lying downposition.

Sleep stages, as in the case of a formal sleep study might require theuse of EEG data from the EEG sensors, however, arousals or awakeningscan be derived from the posture sensor. These would be instances wherethe patient transitioned from one to another posture and depending onthe period of time between the beginning of the transition thetransition can be characterized as an arousal or awakening. Gross motiondata from a motion sensor, consistent with for example walking to thebathroom, or other data can also be overlaid on the data from theposture detector to further assist in classifying the detected movementsor change in posture as an awakening or an arousal.

Respiration rate may be derived by a number of methods. As noted above,a three-axis accelerometer may be tuned to the vibrations of the lungs.By such tuning the change in position of the sensor 50 can be plottedand normalized to provide a respiration rate for the patient. FurtherECG data, as might be acquired from ECG sensors is known to beproportional to respiration rate. In this way as the ECG baselineshifts, as a result of increased heart rate, a proportion change inrespiration rate can be determined. Similarly, an optical sensor, suchas the reflectance blood-oxygen saturation sensor described above tomeasure blood-oxygen saturation levels may also be employed to determinea pulse transit time. A shift in this transit time is also known to beproportional with a chance in respiration rate. For both the ECGbaseline and optical sensor baseline shifts, a normal range of both ofthese values for the patient while sleeping may be required to determinethese changes in respiration rate.

With respect to the respiration rate, any or all of these respirationrates may be employed to develop an AHI value. By comparing changes inthe lung vibration, and changes in the baseline of the ECG and pulsetransit times, an initial approximation of instances of an apnea can beidentified. When any of these occur, the blood-oxygen saturation levelsensor can be triggered to record the blood-oxygen saturation level fora given period of time following the event (assuming it is not beingconstantly monitored). Where a change in respiration rate is observed,if it is followed by a drop in blood-oxygen saturation level, it canreasonably be identified as an apnea, as described above with respect toTable 1. As those are measured on any given night's sleep and over thecourse of days, weeks, and years the development of and the incidence ofsleep apnea can be assessed and actively monitored by health careproviders in coordination with the treatment of the co-morbid heartconditions.

Though described herein largely in the context of sensors 50 that formpart of the implantable device 10, this instant disclosure is not solimited. As noted elsewhere one or more of the sensors including the EEGsensors, the leg movement sensors, the ECG sensor, the blood-oxygensaturation level sensor, and others may be external sensors 100 (FIG. 2)formed external to the patient and the implantable device withoutdeparting from the scope of the disclosure. These external sensors 100may be in communication the external programmer 90 or directly with aremote server (e.g., a cloud-based data system).

A further aspect of the disclosure is described in connection with FIGS.2 and 3 in which a simplified diagram of a system 200 is depicted, and amethod of the systems operation are described. The system 200 includesan implantable device 10, an external programmer 90, one or moreexternal sensors 100, a remote server 202 in communication with theexternal programmer 90, external sensors 100, and a remote computer 204.Those of ordinary skill in the art will appreciate that the remotecomputer 204 may be an external programmer 90, particularly oneconfigured for use by a health care provider.

Following implantation of the implantable device 10, (step 700) the datacollected from sensor 50 is downloaded to the external programmer 90(step 710). This data from the sensor 50 may be combined with variousself-reported data that a user may input via a user interface on theexternal programmer 90 (step 720). In one embodiment of the disclosurethe external programmer 90, or another device (not shown) incommunication with the server 202, presents the patient with a userinterface. The user interface may be presented to the user on a periodicbasis including daily, weekly, bi-weekly, or monthly. In accordance,with the daily embodiment, the user interface may request that thepatient input various self-reporting data. Data from external sensors100 or other appliances may also be reported either to the externalprogrammer 90 or directly to the remote server 202.

As noted above, the sensor 50 can provide a variety of data dependentupon how it is configured. The sensor 50 can be a motion sensor, heartrate detector, ECG sensor, EEG sensor, posture detector, blood-oxygensaturation detector, respiration rate detector, leg movement sensor, andothers. These sensors may be formed of various sub-components including,but not limited to accelerometers tuned to detect specific typesmovement and vibrations as disclosed elsewhere herein.

As one example using the posture detection data, either alone or incombination with heart rate or respiration rate, a sleep start and endtime may be determined. Using one or more accelerometers and a varietyof bandpass filtering position, activity (arousals vs awakenings), sleepstages, respiration rate, and heart rate can be collected. This data canbe reported to the control circuit 20 and stored in memory 30 at leasttemporarily. The external programmer 90 can be set to automaticallyinterface with the implantable 10 every day, every hour, or at anotherperiodic or scheduled interval. The external programmer 90 downloads thesensor data via the telemetry circuit 60 (step 710) and receives theexternal sensor data and self-reported data at step 720. The externalprogrammer may optionally communicate the sensor data from theimplantable device and any and self-reported data entered via theuser-interface to the server 202 (step 725).

Either the server 202 or the external programmer 90 may include thereonone or more software applications. One of these applications may reviewthe data received from the external programmer 90 and assess whether thepatient having the implantable device 10 shows indications of sufferingfrom sleep apnea. For example, a patient who registers a low sleepefficiency (TST/TRT) value, a relatively high number of arousals orawakenings, an AHI value of greater than 15, and drops in blood-oxygensaturation levels following each occurrence of an apnea would providestrong indication that the patient suffers from at least moderate sleepapnea. The application running on the external programmer 90 or server202 may analyze these and other data at step 730 and report anassessment to a health care provider via remote computer 204 at step 740or directly to the patient via the user interface on the externalprogrammer 90 at steps 750. This collection of data and determining of asleep score (steps 710-730) may be iterative repeated prior to advancingto the next step.

Either the healthcare provider, accessing the remote computer 204, canreceive the assessment from the server 202 via the remote computer. Thismay be as part of assessing other data related to the patient. Forexample, where the implantable device 10 is pacemaker, the health careprovider may periodically analyze the heart rhythms and interventionalactions of the pacemaker. On a user interface presented to the healthcare provider via the remote computer 204, in addition to the standardheart related data related directly to the implantable device 10, analert or other indication may be presented to the health care providerindicating that the application has determined that the patient maysuffer from to common comorbidity of sleep apnea.

The remote computer 204 also provides access to the raw data andcomputed data derived from the data collected by the sensor 50 and fromexternal sensors 100 (described above). Thus, the health care providercan analyze the collected and computed data in much the same manner as ahealth care provider might analyze the data collected during atraditional sleep study, as described above.

Whether relying on the indication provide by the application running onthe server 202 or based on the health care provider's own assessment ofthe data the health care provider can initiate communications with thepatient. As will be appreciated the communication can range from relyingsolely on the data collected via the sensor 50 of the implantable device10 and external sensors 100 to start a treatment regimen for sleep apneato scheduling a formal sleep study.

Similarly, the application running on the external programmer 90 canpresent one or more user interfaces to the patient where an initialassessment of the patient's likelihood of suffering from sleep apnea canbe indicated. This may include an indication of the sleep score thepatient received for the prior night's sleep, historical comparison oftheir sleep score and even access to some or all of the raw data fromwhich the sleep score is derived. Further, the user interface maypresent a suggestion to contact their health care provider, anopportunity to make an appointment with their health care provider, oreven access to emergency services if warranted. In addition, even ininstances where the sleep score and other determinations are made on theexternal programmer 90, the external programmer may nonetheless be incommunication with the server 202 to enable further processing andstorage of the data the external programmer 90 has analyzed.

In a further aspect of the disclosure, the server 202 may collect or bein communication one or more further servers receiving similar data fromother patients. The entirety of the collected data may then be analyzedby one or more neural networks to assess the combined data and toidentify patterns within the data to provide indications to health careproviders related to both an individual patient that may requiretreatment and therapy, and to provide a global assessment of a largerpopulation of patients. Some of these patients will have similarcomorbidities, and others will not. By further assessment of the datathe neural network can seek out similar groups of patients and provideinformation to health care providers regarding the likelihood of sleepapnea even before implantation of the implantable device based on thesesimilarities (e.g., age, demographics, weight, heart disease, bloodpressure, etc.). Further, the data from the implantable devices can beconstantly assessed by the neural networks to assess the population ofpatients having implantable devices to diagnose sleep apneaco-morbidities. Additionally or alternatively, the server 202 mayinclude one or more applications employing fuzzy logic to analyze thedata from both an individual and from the broader community of patients(step 730).

As a further aspect of the present disclosure, prior to implantation ofan implantable device 10, the patient may have already undergone apatient assessment of sleep apnea with their health care provider.During this assessment a variety of self-reported issues may beidentified including daytime sleepiness, interrupted snoring, gasping,co-morbidities, etc. The data related to these issues may be stored onthe server 202 as part of the patient electronic medical records (EMR),these data may also be analyzed as part of the application's assessmentof the data received from sensor 90. Further, the EMR may include theresults of a prior sleep study undertaken by the patient. These data maybe recorded by a remote computer 204, either directly or via additionalhardware, and saved to the remote server 202.

As will be appreciated, sleep apnea is a degenerative disease in that itmanifests itself and worsens over time. Thus, even if an in initialsleep study is inconclusive, or does not result in treatment for sleepapnea, over time the patient's condition may worsen and requiretreatment as a result of or in conjunction with the worsening of theirco-morbid conditions.

Though generally having been described herein as having been undertakenat the server 202, any of the calculations and analyses of the sensordata from sensor 50 and described herein can be undertaken by thecontrol circuit 20 or by an application running on the externalprogrammer 90. In this manner the results of these calculations, alongwith any of the direct sensor data may be displayed to a patient or ahealth care provider on the external programmer 90 as part of a userinterface displayable therein. This may include an indication to thepatient that they display symptoms of suffering from sleep apnea andshould seek attention from their health care provider. Similarly, evenif the calculations and analyses are performed by one or moreapplications running on the server 202, because the server 202 is incommunication with external programmer 90 the results of thosecalculations and analyses may be transmitted back to the externalprogrammer 90 and presented to the patient on a user interfacedisplayable thereon. Again, this may include an indication to thepatient that they appear to display symptoms of sleep apnea and shouldseek attention from their health care provider.

It should be understood that, depending on the example, certain acts orevents of any of the methods described herein can be performed in adifferent sequence, may be added, merged, or left out altogether (e.g.,not all described acts or events are necessary for the practice of themethod). Moreover, in certain examples, acts or events may be performedconcurrently, e.g., through multi-threaded processing, interruptprocessing, or multiple processors, rather than sequentially. Inaddition, while certain aspects of this disclosure are described asbeing performed by a single module or unit for purposes of clarity, itshould be understood that the techniques of this disclosure may beperformed by a combination of units or modules associated with, forexample, a medical device.

In one or more examples, the functions described may be implemented inhardware, software, firmware, or any combination thereof. If implementedin software, the functions may be stored as one or more instructions orcode on a computer-readable medium and executed by a hardware-basedprocessing unit. Computer-readable media may include computer-readablestorage media, which corresponds to a tangible medium such as datastorage media (e.g., RAM, ROM, EEPROM, flash memory, or any other mediumthat can be used to store desired program code in the form ofinstructions or data structures and that can be accessed by a computer).

Instructions may be executed by one or more processors, such as one ormore digital signal processors (DSPs), general purpose microprocessors,application specific integrated circuits (ASICs), field programmablelogic arrays (FPGAs), or other equivalent integrated or discrete logiccircuitry. Accordingly, the term “processor,” as used herein may referto any of the foregoing structure or any other structure suitable forimplementation of the techniques described herein. Also, the techniquescould be fully implemented in one or more circuits or logic elements.

Thus, an implantable medical device system has been presented in theforegoing description with reference to specific examples. It is to beunderstood that various aspects disclosed herein may be combined indifferent combinations than the specific combinations presented in theaccompanying drawings. It is appreciated that various modifications tothe referenced examples may be made without departing from the scope ofthe disclosure and the following claims.

We claim:
 1. A method of assessing a patient for sleep apnea comprising:receiving sensor data from a device implanted in a patient for treatmentof a heart related disease at an external programmer; transmitting thereceived sensor data to a remote server; analyzing the received data atthe server; and transmitting to a remote computer an assessment of thereceived sensor data, wherein the assessment includes an evaluation ofsleep apnea for the patient.
 2. The method of claim 1, furthercomprising receiving sensor data from an external sensor.
 3. The methodof claim 1, further comprising receiving self-reported data.
 4. Themethod of claim 1, wherein the sensor data includes data indicative ofthe posture of the patient, motion data of the patient,electroencephalogram (EEG) data, electrocardiogram (ECG) data, ApneaHypopnea Index (AHI) data or blood-oxygen saturation data.
 5. The methodof claim 1, wherein the sensor data includes data from one or morethree-axis accelerometers.
 6. The method of claim 1, wherein the sensordata includes respiration rate data, heart rate data, total sleep timedata, sleep efficiency data, sleep stage data, arousals data, orawakenings data.
 7. The method of claim 1, wherein the implanted deviceselected from the group consisting of a pacemaker, an implantablecardiac defibrillators (ICD), a cardiac resynchronization therapy (CRT)device, and an implantable neurostimulator (INS).
 8. The method of claim1, further comprising a neural network performing the analysis of thereceived data.
 9. A system comprising: an implantable device including asensor, a telemetry circuit and a memory; an external programmer incommunication with the telemetry circuit and configured to receive datacollected by the sensor and stored in the memory; a server, including aprocessor, in communication with the external programmer and storingthereon an application including instructions that when executed by theprocessor executes steps of: receiving the data collected by the sensorfrom the external programmer; and analyzing the received data collectedby the sensor; and transmitting to a remote computer an assessment ofthe received sensor data, wherein the assessment includes an evaluationof sleep apnea for patient in which the implantable device has beenimplanted.
 10. The system of claim 8, further comprising one or moreexternal sensors configured to transmit sensor data to the server or theexternal programmer.
 11. The system of claim 8, further comprising auser-interface presented on the external programmer and configured toreceive self-reported data.
 12. The system of claim 8, wherein thesensor outputs data indicative of the posture of the patient, motion ofthe patient, an electroencephalogram (EEG), an electrocardiogram (ECG),an Apnea Hypopnea Index (AHI) or blood-oxygen saturation.
 13. The systemof claim 8, wherein the sensor is comprised of one or more three-axisaccelerometers.
 14. The system of claim 8, wherein the sensor outputsdata indicative of respiration rate, heart rate, total sleep time, sleepefficiency, sleep stage, arousals, or awakenings.
 15. The system ofclaim 8, wherein the implanted device selected from the group consistingof a pacemaker, an implantable cardiac defibrillators (ICD), a cardiacresynchronization therapy (CRT) device, and an implantableneurostimulator (INS).
 16. The system of claim 8, further comprising aneural network performing the analysis of the received data at theserver.
 17. A computer readable recording medium storing thereoninstructions that when executed by a processor and cause the processorto execute the steps of: receiving sensor data from an externalprocessor, the sensor data having been collected by an implanted deviceconfigured for treatment of a heart related disease; analyzing thereceived sensor data; and transmitting to a remote computer anassessment of the received sensor data, wherein the assessment includesan evaluation of sleep apnea for a patient in which the implantabledevice has been implanted.
 18. The computer readable recording medium ofclaim 17, wherein the sensor data includes data indicative of theposture of the patient, motion data of the patient, electroencephalogram(EEG) data, electrocardiogram (ECG) data, Apnea Hypopnea Index (AHI)data or blood-oxygen saturation data.
 19. The computer readablerecording medium of claim 17, wherein the sensor data includes data fromone or more three-axis accelerometers.
 20. The computer readablerecording medium of claim 17, wherein the sensor data includesrespiration rate data, heart rate data, total sleep time data, sleepefficiency data, sleep stage data, arousals data, or awakenings data.